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    "# imports\n",
    "\n",
    "import os\n",
    "from dotenv import load_dotenv\n",
    "from openai import OpenAI\n",
    "\n",
    "# If you get an error running this cell, then please head over to the troubleshooting notebook!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b87cadb-d513-4303-baee-a37b6f938e4d",
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   "source": [
    "# Load environment variables in a file called .env\n",
    "\n",
    "load_dotenv(override=True)\n",
    "api_key = os.getenv('OPENAI_API_KEY')\n",
    "\n",
    "# Check the key\n",
    "\n",
    "if not api_key:\n",
    "    print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
    "elif not api_key.startswith(\"sk-proj-\"):\n",
    "    print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
    "elif api_key.strip() != api_key:\n",
    "    print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
    "else:\n",
    "    print(\"API key found and looks good so far!\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "019974d9-f3ad-4a8a-b5f9-0a3719aea2d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "openai = OpenAI()\n",
    "\n",
    "# If this doesn't work, try Kernel menu >> Restart Kernel and Clear Outputs Of All Cells, then run the cells from the top of this notebook down.\n",
    "# If it STILL doesn't work (horrors!) then please see the Troubleshooting notebook in this folder for full instructions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "00743dac-0e70-45b7-879a-d7293a6f68a6",
   "metadata": {},
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   "source": [
    "# Step 1: Create your prompts\n",
    "\n",
    "system_prompt = \"Eres un analista acostumbrado a trabajar con correos electrónicos que contiene un gran conocimiento sobre la mejor manera de resumir contenido releveante \\\n",
    "dejando de lado cualquier información que no despierte interés o no sea el tema principal del correo. Tu función será leer contenido de correos y definir un listado de las 3 mejores opciones con el formato: Opción *numero de la opción*: *sujeto* Motivo: *que palabras clave dentro del texto has utilizado para llegar a esa conclusion y la relación semántica con tu idea\"\n",
    "user_prompt = \"\"\"\n",
    "Tengo un correo que le quiero enviar a mi profesor pero no se muy bien como llamarlo, ayudame. El correo es el siguiente:\n",
    "Hola profe,\n",
    "Ultimamente estoy disfrutando mucho sus clases y la información que presenta me parece muy importante. Este fin de semana me voy de vacaciones y no podré\n",
    "ir a sus clases la semana que viene. Me gustaría si pudiera pasarme los pdfs de la siguiente semana para echarle un vistazo por mi cuenta durante mi ausencia en Francia.\n",
    "\n",
    "Un saludo,\n",
    "Daniel.\n",
    "\"\"\"\n",
    "\n",
    "# Step 2: Make the messages list\n",
    "\n",
    "messages = [{\"role\" : \"system\" , \"content\": system_prompt},\n",
    "            {\"role\": \"user\", \"content\": user_prompt}]\n",
    "\n",
    "# Step 3: Call OpenAI\n",
    "\n",
    "response = openai.chat.completions.create( \n",
    "    model = \"gpt-4o-mini\",\n",
    "    messages = messages)\n",
    "\n",
    "# Step 4: print the result\n",
    "\n",
    "print(response.choices[0].message.content)"
   ]
  }
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